International conference on software engineering and knowledge engineering: Session chair

The Thirtieth International Conference on Software Engineering and Knowledge Engineering (SEKE 2018) will be held at the Hotel Pullman, San Francisco Bay, USA, from July 1 to July 3, 2018. SEKE2018 will also be dedicated in memory of Professor Lofti Zadeh, a great scholar, pioneer and leader in fuzzy sets theory and soft computing. The conference aims at bringing together experts in software engineering and knowledge engineering to discuss on relevant results in either software engineering or knowledge engineering or both. Special emphasis will be put on the transference of methods between both domains. The theme this year is soft computing in software engineering & knowledge engineering. Submission of papers and demos are both welcome

Knowledge Engineering in Search Engines

With large amounts of information being exchanged on the Internet, search engines have become the most popular tools for helping users to search and filter this information. However, keyword-based search engines sometimes obtain information, which does not meet user’ needs. Some of them are even irrelevant to what the user queries. When the users get query results, they have to read and organize them by themselves. It is not easy for users to handle information when a search engine returns several million results. This project uses a granular computing approach to find knowledge structures of a search engine. The project focuses on knowledge engineering components of a search engine. Based on the earlier work of Dr. Lin and his former student [1], it represents concepts in the Web by simplicial complexes. We found that to represent simplicial complexes adequately, we only need the maximal simplexes. Therefore, this project focuses on building maximal simplexes. Since it is too costly to analyze all Web pages or documents, the project uses the sampling method to get sampling documents. The project constructs simplexes of documents and uses the simplexes to find maximal simplexes. These maximal simplexes are regarded as primitive concepts that can represent Web pages or documents. The maximal simplexes can be used to build an index of a search engine in the future

Towards Knowledge-Intensive Software Engineering

Postprin

Knowledge modeling for software design

This paper develops a modeling framework for systems engineering that encompasses systems modeling, task modeling, and knowledge modeling, and allows knowledge engineering and software engineering to be seen as part of a unified developmental process. This framework is used to evaluate what novel contributions the 'knowledge engineering' paradigm has made and how these impact software engineering

Knowledge Engineering and Intelligence Gathering

A process of intelligence gathering begins when a user enters a query into the system. Several objects can match the result of a query with different degrees of relevance. Most systems estimate a numeric value about how well each object matches the query and classifies objects according to this value. Many researches have focused on practices of intelligence gathering. In knowledge engineering, knowledge gathering consists in fiding it from structured and unstructured sources in a way that must represent knowledge in a way that facilitates inference. DOI: 10.13140/RG.2.2.32191.1552

Knowledge Engineering Technique for Cluster Development

After the concept of industry cluster was tangibly applied in many countries, SMEs trended to link to each other to maintain their competitiveness in the market. The major key success factors of the cluster are knowledge sharing and collaboration between partners. This knowledge is collected in form of tacit and explicit knowledge from experts and institutions within the cluster. The objective of this study is about enhancing the industry cluster with knowledge management by using knowledge engineering which is one of the most important method for managing knowledge. This work analyzed three well known knowledge engineering methods, i.e. MOKA, SPEDE and CommonKADS, and compares the capability to be implemented in the cluster context. Then, we selected one method and proposed the adapted methodology. At the end of this paper, we validated and demonstrated the proposed methodology with some primary result by using case study of handicraft cluster in Thailand

Collaborative Engineering Environments. Two Examples of Process Improvement

Companies are recognising that innovative processes are determining factors in competitiveness. Two examples from projects in aircraft development describe the introduction of collaborative engineering environments as a way to improve engineering processes. A multi-disciplinary simulation environment integrates models from all disciplines involved in a common functional structure. Quick configuration for specific design problems and powerful feedback / visualisation capabilities enable engineering teams to concentrate on the integrated behaviour of the design. An engineering process management system allows engineering teams to work concurrently in tasks, following a defined flow of activities, applying tools on a shared database. Automated management of workspaces including data consistency enables engineering teams to concentrate on the design activities. The huge amount of experience in companies must be transformed for effective application in engineering processes. Compatible concepts, notations and implementation platforms make tangible knowledge like models and algorithms accessible. Computer-based design management makes knowledge on engineering processes and methods explicit

Engineering geology maps of the UK

School and university students of geology, engineering geology and geotechnical engineering generally have less knowledge of engineering geological conditions than those who have had experience of hands-on research or practice. In the UK, the number of geology, geoscience and earth science departments has reduced over the past 25 years. Engineering geology has a very weak academic base and geology is taught less to civil engineering students than previously